It’s 3:00 PM. Anna opens Claude and types: “Does my policy cover today’s repair, and when is my next service inspection?”. Instead of calling customer support, she no longer searches her inbox or logs into a portal. She simply wants a direct answer, right here, right now.
However, this is no exception – users have fundamentally shifted where they go for answers. For instance, they ask ChatGPT what’s included in their contract, while relying on Claude for appointment times, and consulting Copilot to see if their points are enough for a discount. Rather than searching a traditional website, they simply type a prompt.
If your app isn’t connected to AI assistants, your product simply doesn’t exist in that conversation. As a result, the user gets a generic response, a guess, or complete silence.
Luckily, MCP (Model Context Protocol) changes that completely. It seamlessly connects your product’s data and actions to AI assistants like ChatGPT, Claude, and Copilot. Consequently, one integration serves every assistant.
The scale is not small. 900 million people use ChatGPT every week. 50% of employed Americans used AI at work in Q1 2026. Microsoft 365 Copilot has 20 million paid enterprise seats.
Not sure where your product fits? Book a call. We’ll show you exactly where the gap is.
What MCP actually is
MCP is an open standard that connects AI assistants directly to your systems. As a result, it unlocks real data and real actions, making your product accessible wherever your users are.
Before MCP, every AI assistant required its own connection to your product. Therefore, one assistant meant one custom integration. In contrast, MCP replaces these separate connections with one standard layer that allows AI assistants to connect to your product effortlessly.
For example, Claude, ChatGPT, Microsoft Copilot, Gemini, and GitHub Copilot all support MCP today. As a result, it is rapidly becoming the universal standard for connecting AI assistants to products and services.
What this means for your product
Your users can now discover your product through AI assistants, get answers from your systems in real time, and return to your app when they need to take action.
For anything that requires an action: booking, purchasing, submitting or redeeming. The assistant can direct the user back to your app to complete it.
MCP gives your product a new entry point: users discover it through AI assistants and return to your app to act.
See it in action
Imagine an e-commerce platform with product data available through an API. With agentic integration, an AI assistant can retrieve product details, check availability or help a user find the right product: turning a simple API connection into an interactive product experience. When an action is required, such as adding an item to a cart or completing a purchase, the user returns to your app to finish it.
MCP Server -stop exposing only raw API endpoints You will expose an agentic-friendly layer with actions that agent can perform getDetails, getInvoices, addToBasket.
MCP UI – go beyond text-only answers. Instead of returning text message, you can render card, carousels with images, tables and more.
Three things MCP makes possible
1. MCP Server – make your product visible to AI
Right now, the world’s most-used AI assistants don’t know your product exists. For this reason, they can’t read your data or trigger your actions. They simply answer with whatever generic information they have—not what your users actually need.
Fortunately, an MCP Server changes that. It exposes a defined subset of your data and actions through a standard protocol, including account data, product catalogues, transaction histories, service records, and policy details. Consequently, AI assistants can now reach your systems in real time.
Importantly, your existing infrastructure stays unchanged. You don’t need to rebuild your platform. Instead, you add a server layer that speaks the language AI assistants understand. As a result, your product becomes an active part of every conversation where it belonged all along.
Forrester projects that 30% of enterprise application vendors will launch MCP servers in 2026. In categories where one product builds this first, the others face years of catch-up. They handed over that head start for free.
2. MCP UI – your app stays in the relationship
MCP UI is a new presentation layer that goes beyond simple text, allowing you to show users more than just an answer. By rendering rich, interactive content like cards, carousels, tables, and calendars – directly within the chat interface, you transform a static conversation into a functional experience. This bridges the gap between the AI’s response and your application’s capabilities: users can browse rewards or check availability instantly without leaving the chat. AI handles the query; your UI handles the interaction, keeping the user relationship directly within your product.
3. ChatGPT / Claude App – your product inside the world’s biggest platforms
Imagine your product being available to every ChatGPT user. It becomes discoverable without searching, accessible without downloading, and usable by AI agents acting on your users’ behalf.
However, building a presence inside ChatGPT and Claude isn’t a distant future scenario. In fact, it is available today. A dedicated app within these platforms makes your product an integral part of the AI ecosystem. Therefore, users who never found you before can easily reach you, while agents completing tasks on their behalf can access your services as well.
Gartner projects that 40% of enterprise applications will include task-specific AI agents by the end of 2026. Products without MCP will be invisible to that layer. The same way products without mobile apps were invisible to mobile users in 2010. That window closed fast. This one will too.
What this looks like in practice
Banking and financial services
A retail bank customer asks their AI assistant about their balance, recent transactions, or loan eligibility. The MCP Server returns authenticated answers from the bank’s core systems in real time. The MCP UI directs the user to the banking app to act: transfer, apply, or confirm. The AI handles the question. The app handles the transaction.
No custom integration built. No platform rebuilt. One protocol layer added to existing APIs.
AI-assisted service operations reduce average handling times by 20–40%. Users arrive knowing what they want. The conversation already started. Your app closes it.
Healthcare
The same pattern runs across regulated industries. A patient asks their AI assistant about available appointment slots. The MCP Server retrieves real-time availability from the scheduling platform. The MCP UI directs them to the patient portal to confirm the booking. Prior authorisation requests pulled from clinical systems and submitted electronically in minutes instead of days. AI that works across EHRs, patient portals, and lab systems. No rebuilding required.
Insurance
A policyholder asks their AI assistant what’s covered before filing a claim. The MCP Server answers directly from policy data: accurate, compliant, without a call to the contact centre. The MCP UI sends them to the claims app to file.
For insurers operating under FINMA data residency requirements, the July 2026 MCP specification delivers the controls that matter: hardened authorisation aligned with OAuth 2.0, and a stateless architecture built for enterprise deployment. The integration runs over authenticated API calls. No data leaves your infrastructure.
Retail and e-commerce
In retail and e-commerce, the entry point shifts. A loyalty member could ask ChatGPT about their points balance and available rewards. A shopper asks Claude about delivery status or return eligibility. The MCP Server answers from your platform. The MCP UI directs them back to your app to redeem, purchase, or act.
From idea to production
Want to see what MCP looks like for your product? Book a call. We’ll map your product against the three MCP layers and take you into a Discovery Workshop to define what to build first.
The window
MCP reached production stability in late 2025. Claude, Copilot, and ChatGPT all support it – ChatGPT through native MCP integration, separate from GPT Actions.
Every category will have a first mover. The first banking app AI assistants learn to reach. The first insurance product patients find through Claude. The first loyalty platform ChatGPT knows how to query.
The next question isn’t whether your users will interact with AI assistants. It’s whether your product will be there when they do.
Not sure which MCP layer fits your product first? Book a call. We’ll assess your stack and take you into a Discovery Workshop where we scope the first concrete step together.
Sources: Gallup: Rising AI Adoption Spurs Workforce Changes · Stacklok: State of MCP in Financial Services 2026 · Forrester Predictions 2026 · Gartner: 40% Enterprise Apps AI Agents 2026 · The Financial Brand: AI ROI in Financial Services · MCP 2026 Specification Release Candidate
